urllib3.exceptions.MaxRetryError: HTTPSConnectionPool(host='huggingface.co', port=443): Max retries exceeded with url: /openai/clip-vit-large-patch14/resolve/main/vocab.json (Caused by ProxyError('Your proxy appears to only use HTTP and not HTTPS, try changing your proxy URL to be HTTP. ...
fromPILimportImageimportrequestsfromtransformersimportCLIPProcessor, CLIPModel model = CLIPModel.from_pretrained("openai/clip-vit-large-patch14") processor = CLIPProcessor.from_pretrained("openai/clip-vit-large-patch14") url ="http://images.cocodataset.org/val2017/000000039769.jpg"image = Image.open...
分析日志,划重点,缺少工具包openai/clip-vit-large-patch14 OSError: Can't load tokenizer for 'openai/clip-vit-large-patch14'. If you were trying to load it from 'https://huggingface.co/models', make sure you don't have a local directory with the same name. Otherwise, make sure 'openai...
这个错误提示说明加载'openai/clip-vit-large-patch14'模型的分词器(tokenizer)出现了问题。可能的原因是无法访问分词器文件。您可以尝试使用以下代码下载分词器文件:stylusimport openaiopenai.api_key = "YOUR_API_KEY"model_name = "openai/clip-vit-large-patch14"tokenizer = openai.api.Completion.create(engine...
CLIPTextModelclassText_Encoder(nn.Module):'''clip-vit-large-patch14为模型参数,需要提前单独下载并...
本实验通过在ECS上从零开始部署Stable Diffusion来进行AI绘画创作,开启AIGC盲盒。 关于openai/clip-vit-large-patch14的报错,要手动下载,并且要修改源文件路径。 源文件 vim repositories/stable-diffusion-stability-ai/ldm/modules/encoders/modules.py 找到其中的openai/clip-vit-large-patch14 ...
绘世启动报错!..报错内容Can't load tokenizer for 'openai/clip-vit-large-patch14'. If you were trying to load it from '(有
I have tried troubleshooting this issues and asking others for help, but I can't seem to get this issue fixed. Creating model from config: C:\Users\Kevin\Downloads\AI Art\stable-diffusion-webui\configs\v1-inference.yaml LatentDiffusion: ...
"./models/openai/clip-vit-large-patch14") 1. 2. 3. 5、加载和显示图像 为了加载图像,我们将使用PIL库并导入Image类。使用 AI检测代码解析 Image.open 1. 加载图像,并指定图像的路径。 AI检测代码解析 from PIL import Image image = Image.open("./occupiers.png") ...
网络结构如下图所示(文本编码器为BERT,视觉编码器为ViT): VLMo应用于下游任务: 预训练的base版本使用64个Nvidia Tesla V100 32GB GPU花了2天来训练,large版本使用128个Nvidia Tesla V100 32GB GPU花了三天进行训练。 多模态预训练模型串烧1:CLIP、ViLT、ALBEF、VLMomp.weixin.qq.com/s/bUkQA27OphCleiqREM...